Hello, I'm

Danny Schantz

Nuclear Engineering Researcher & Machine Learning Developer

Graduate student at the University of Florida, developing Physics-Informed Neural Networks to solve complex plasma physics problems.

About Me

Bridging the gap between theoretical physics and computational solutions

DS

Nuclear Engineering

University of Florida

I'm a Nuclear Engineering graduate student at the University of Florida with a background in Chemical Engineering. My research focuses on developing innovative computational methods to solve complex problems in plasma physics.

Currently, I work as a Research Assistant in the Plasma and Fusion Group, where I develop Physics-Informed Neural Networks (PINNs) to solve the relativistic Fokker-Planck equation. I leverage UF's HiPerGator HPC resources for large-scale model training.

My work combines deep expertise in plasma physics with cutting-edge machine learning techniques to predict primary runaway electron formation rates and model Dreicer generation mechanisms.

Plasma Physics

Researching runaway electron dynamics and Fokker-Planck equations

Machine Learning

Developing Physics-Informed Neural Networks (PINNs) for scientific computing

Software Development

Building deep learning workflows with Python, PyTorch, and HPC systems

Research

Investigating Dreicer generation mechanisms and electron formation rates

Experience & Education

My academic and professional journey in nuclear engineering and computational research

Work Experience

Graduate Research Assistant

Aug 2025 – Present

Plasma and Fusion Group, University of Florida

  • Developing Physics-Informed Neural Networks to solve plasma physics partial differential equations using UF HiPerGator HPC resources
  • Designing deep learning workflows in Python and PyTorch to model plasma dynamics in tokamak fusion devices
  • Focus on relativistic electron formation and electron distribution evolution

Student Assistant – Reactor Operations

Sep 2025 – Present

University of Florida Training Reactor (UFTR)

  • Completing NRC-certified training curriculum in preparation for Reactor Operator licensure
  • Acquiring knowledge of reactor systems including radiation detection, thermal-hydraulics, instrumentation and controls
  • Assisting with daily reactor operations as a qualified second person and performing instrumentation maintenance

Materials Science R&D Intern

Jan 2024 – Aug 2025

Mackinac Technology Company

  • Led experimental design and process optimization for a DOE-funded Liquid Silicone Rubber window project
  • Eliminated 99.6% of bubble formation while increasing surface uniformity by 92%
  • Conducted literature reviews and contributed to SBIR grant writing efforts for ongoing research funding

Education

Master of Science in Nuclear Engineering Sciences

Aug 2025 – May 2027

University of Florida

  • Thesis Track with 4.0 GPA
  • Research on runaway electron generation in spherical tokamak plasmas under Dr. McDevitt
  • Focus on Physics-Informed Neural Networks for fusion applications

Bachelor of Science in Engineering (Chemical Engineering)

Aug 2021 – May 2025

Calvin University

  • GPA: 3.5
  • Strong foundation in thermodynamics and transport phenomena
  • Background in mathematical modeling and computational methods

Featured Projects

A selection of my research projects and personal work in computational physics and software development

Physics-Informed Neural Networks for Plasma Physics

Developing PINNs to solve the relativistic Fokker-Planck equation for modeling runaway electron dynamics in fusion plasmas. Utilizes PyTorch and HiPerGator HPC for large-scale training.

PythonPyTorchHPCPhysicsDeep Learning

HardlyHard

A project focused on converting difficult-to-understand research into simple, actionable, and teachable information. Making complex scientific concepts accessible.

ResearchEducationScience Communication

Dreicer Generation Modeling

Deep learning workflows designed to accurately model Dreicer generation mechanisms and predict primary runaway electron formation rates in plasma systems.

Machine LearningPlasma PhysicsNumerical Methods

Other Notable Projects

Full-Stack Web Application

A complete web application with separate frontend and backend repositories, demonstrating full-stack development capabilities.

JavaScriptReactNode.jsFull-Stack

Personal Portfolio Website

This very website! Built with Next.js, TypeScript, and Tailwind CSS. Features a modern, responsive design with smooth animations.

Next.jsTypeScriptTailwind CSSReact

Interactive Coding Challenges

Collection of coding challenges and exercises from NEXT Academy Coding Bootcamp, showcasing problem-solving skills and JavaScript proficiency.

JavaScriptProblem SolvingAlgorithms

Skills & Technologies

A comprehensive toolkit spanning scientific computing, machine learning, and software development

Programming Languages

PythonJavaScriptTypeScriptMATLABC++

Machine Learning & AI

PyTorchTensorFlowPhysics-Informed Neural NetworksDeep LearningPredictive Analytics

Scientific Computing

Numerical MethodsHPC (HiPerGator)Plasma Physics SimulationsFokker-Planck SolversParallel Computing

Domain Expertise

Nuclear EngineeringPlasma PhysicsChemical EngineeringThermodynamicsTransport Phenomena

Tools & Technologies

GitLinuxDockerJupyterLaTeX

Soft Skills

Technical WritingResearchProblem SolvingPresentationCollaboration
M.S.
Degree in Progress
UF
University of Florida
PINNs
Research Focus
HPC
Computing Resources

Get In Touch

I'm always open to discussing research opportunities, collaborations, or just having a conversation about physics and machine learning.

Contact Information

dannyschantz1@icloud.com
Gainesville, Florida

Connect with me

Send a Message

Or email me directly at dannyschantz1@icloud.com